In this article, we present the first Systematization of Knowledge (SoK) on constructing Layer Two (L2) solutions for Bitcoin. We carefully examine a representative subset of ongoing Bitcoin L2 solutions (40 out of 335 extensively investigated cases) and provide a concise yet impactful identification of six classic design patterns through two approaches (i.e., modifying transactions and creating proofs). Notably, we are the first to incorporate the inscription technology (emerged in mid-2023), along with a series of related innovations. We further establish a reference framework that serves as a baseline criterion ideally suited for evaluating the security aspects of Bitcoin L2 solutions, and which can also be extended to broader L2 applications. We apply this framework to evaluate each of the projects we investigated. We find that the inscription-based approaches introduce new functionality (i.e., programability) to Bitcoin systems, whereas existing proof-based solutions primarily address scalability challenges. Our security analysis reveals new attack vectors targeting data/state (availability, verification), assets (withdrawal, recovery), and users (disputes, censorship).
Open access
3 source records
Blockchain Technology Applications and Security
Retinal Imaging and Analysis
Advanced Steganography and Watermarking Techniques
Mark C. Ballandies, Dino Carpentras, Evangelos Pournaras
Decentralized autonomous organizations (DAOs) have transformed organizational structures by shifting from traditional hierarchical control to decentralized approaches, leveraging blockchain and cryptoeconomics. Despite managing significant funds and building global networks, DAOs face challenges like declining participation, increasing centralization, and inabilities to adapt to changing environments, which stifle innovation. This paper explores DAOs as complex systems and applies complexity science to explain their inefficiencies. In particular, we discuss DAO challenges, their complex nature, and introduce the self-organization mechanisms of collective intelligence, digital democracy, and adaptation. By applying these mechanisms to refine DAO design and construction, a conceptual framework for assessing a DAO’s viability is created. This contribution lays the foundation for future research at the intersection of complexity science, digital democracy and DAOs.
The popularity of the Internet of Things (IoT) has driven its usage in our homes and industries over the past 10-12 years. However, there have been some major issues related to identity management and ownership transfer involving IoT devices, particularly for consumer IoT devices, e. g. smart appliances such as smart TVs, smart refrigerators, and so on. There have been a few attempts to address this issue; however, user-centric and effective ownership and identity management of IoT devices have not been very successful so far. Recently, blockchain technology has been used to address these issues with limited success. This article presents a Self-sovereign Identity (SSI) based system that facilitates a secure and user-centric ownership management and transfer of consumer IoT devices. The system leverages a number of emerging technologies, such as blockchain and decentralized identifiers (DID), verifiable credentials (VC), under the umbrella of SSI. We present the architecture of the system based on a threat model and requirement analysis, discuss the implementation of a Proof-of-Concept based on the proposed system and illustrate a number of use-cases with their detailed protocol flows. Furthermore, we analyse its security using ProVerif, a state-of-the art protocol verification tool and examine its performance.
Ashok Kumar Peepliwall, Hari Mohan Pandey, Surya Prakash, Anand A Mahajan · 7 authors
The COVID-19 pandemic necessitated the emergence of decentralized Clinical Trials (DCTs) due to patient retention, accelerate trials, improve data accessibility, enable virtual care, and facilitate seamless communication through integrated systems. However, integrating systems in DCTs exposes clinical data to potential security threats, making them susceptible to theft at any stage, a high risk of protocol deviations, and monitoring issues. To mitigate these challenges, blockchain technology serves as a secure framework, acting as a decentralized ledger, creating an immutable environment by establishing a zero-trust architecture, where data are deemed untrusted until verified. In combination with Internet of Things (IoT)-enabled wearable devices, blockchain secures the transfer of clinical trial data on private blockchains during DCT automation and operations. This paper proposes a prototype model of the Zero-Trust Architecture Blockchain (z-TAB) to integrate patient-generated clinical trial data during DCT operation management. The EigenTrust-based Practical Byzantine Fault Tolerance (T-PBFT) algorithm has been incorporated as a consensus protocol, leveraging Hyperledger Fabric. Furthermore, the Internet of Things (IoT) has been integrated to streamline data processing among stakeholders within the blockchain platforms. Rigorous evaluation has been done to evaluate the quality of the system.
Haozhao Zhang, Zhe Zhang, Zhiqiang Zheng, Varghese Jacob
This paper proposes a new paradigm: generative blockchain, which aims to transform conventional blockchain technology by combining transaction generation and recording, rather than focusing solely on transaction recording. Central to our design is a novel consensus mechanism, Proof-of-Merit (PoM), specifically crafted for environments where businesses must solve complex problems before transactions can be recorded. PoM integrates the generation and recording of transactions within a unified blockchain system, fundamentally differing from prevailing consensus mechanisms that primarily record existing transactions. We demonstrate PoM on a ride service on-demand platform, where the task of solving complex transaction-generating problems is delegated to a pool of independent problem solvers. These solvers generate transactions, and their solutions are selected based on merit. The winning solvers then register these transactions onto the blockchain and are rewarded accordingly. We introduce a Decentralized Control Parameter (DCP) to balance two key performance metrics: efficiency and equity. The applicability of our generative blockchain is illustrated through a ridesharing context, where matchers (solvers) are tasked with matching riders to drivers. We demonstrate PoM's performance and nuanced properties using agent-based simulation, exploring how to find the optimal DCP value to achieve a desirable balance of efficiency and equity in a generative blockchain.
Ishmam Abid, S. M. Zuhayer Anzum Fuad, Mohammad Jabed Morshed Chowdhury, Mehruba Sharmin Chowdhury · 5 authors
The circular economy has the potential to increase resource efficiency and minimize waste through the 4R framework of reducing, reusing, recycling, and recovering. Blockchain technology is currently considered a valuable aid in the transition to a circular economy. Its decentralized and tamper-resistant nature enables the construction of transparent and secure supply chain management systems, thereby improving product accountability and traceability. However, the full potential of blockchain technology in circular economy models will not be realized until a number of concerns, including scalability, interoperability, data protection, and regulatory and legal issues, are addressed. More research and stakeholder participation are required to overcome these limitations and achieve the benefits of blockchain technology in promoting a circular economy. This article presents a systematic literature review (SLR) that identified industry use cases for blockchain-driven circular economy models and offered architectures to minimize resource consumption, prices, and inefficiencies while encouraging the reuse, recycling, and recovery of end-of-life products. Three main outcomes emerged from our review of 41 documents, which included scholarly publications, Twitter-linked information, and Google results. The relationship between blockchain and the 4R framework for circular economy; discussion the terminology and various forms of blockchain and circular economy; and identification of the challenges and obstacles that blockchain technology may face in enabling a circular economy. This research shows how blockchain technology can help with the transition to a circular economy. Yet, it emphasizes the importance of additional study and stakeholder participation to overcome potential hurdles and obstacles in implementing blockchain-driven circular economy models.
Valdemar Vicente Graciano-Neto, Jacson Rodrigues Barbosa, Eliomar Araújo de Lima, Luiza Cintra · 7 authors
Fake News are a contemporary phenomenon with potential devastating effects. For inquiry and auditability purposes, it is essential that the news, once classified as false, can be persisted in an immutable means so that interested parties can query it. Although Blockchain clearly satisfies the main requirements for Fake News Management Software Systems, the prescriptive architectural solutions for that domain that cohabit Blockchain with other technologies in a single proposal still need to be made available. This paper's main contribution is presenting a prescriptive architectural solution for blockchain-based fake news management software systems. The Hoffmeister process for software architecture design is systematically followed to culminate in a software solution for that domain. The implementation of two candidate architectures and a brief simulation-based evaluation show the feasibility of the solution to satisfy the functional and quality requirements.
Decentralized Health Intelligence Network (DHIN) extends the Decentralized Intelligence Network (DIN) framework to address challenges in healthcare data sovereignty and AI utilization. Building upon DIN's core principles, DHIN introduces healthcare-specific components to tackle data fragmentation across providers and institutions, establishing a sovereign architecture for healthcare provision. It facilitates effective AI utilization by overcoming barriers to accessing diverse health data sources. This comprehensive framework leverages: 1) self-sovereign identity architecture coupled with a personal health record (PHR), extending DIN's personal data stores concept to ensure health data sovereignty; 2) a scalable federated learning (FL) protocol implemented on a public blockchain for decentralized AI training in healthcare, tailored for medical data; and 3) a scalable, trustless rewards mechanism adapted from DIN to incentivize participation in healthcare AI development. DHIN operates on a public blockchain with an immutable record, ensuring that no entity can control access to health data or determine financial benefits. It supports effective AI training while allowing patients to maintain control over their health data, benefit financially, and contribute to a decentralized ecosystem. Unique to DHIN, patients receive rewards in digital wallets as an incentive to opt into the FL protocol, with a long-term roadmap to fund decentralized insurance solutions. This approach introduces a novel, self-financed healthcare model that adapts to individual needs, complements existing systems, and redefines universal coverage, showcasing how DIN principles can transform healthcare data management and AI utilization while empowering patients.
Mudathir Muhammad Salahudeen, Muhammad Auwal Mukhtar, Saadu Salihu Abubakar, Salawu I. S
Over time, agriculture is the most consistent activity, and it evolves every day. It contributes to a vast majority of the Gross Domestic Product (GDP) of Nigeria but as ironic as it may be, there is still hunger in significant parts of the country due to low productivity in the agricultural sector and comparison to the geometric population growth. During the first half of 2022, agriculture contributed about 23% of the country's GDP while the industry and services sector had a share of the remaining 77%. This showed that with the high rate of agricultural activities, Nigeria has not achieved food security for the teeming population. and more productivity levels can be attained. Technology can/will assist Nigeria in overcoming global poverty and hunger quicker in both rural and urban areas. Today, there are many types of agricultural technologies available for farmers all over the world to increase productivity. Major technological advancements include indoor vertical farming, automation, robotics, livestock technology, modern greenhouse practices, precision agriculture, artificial intelligence, and blockchain. Mobile phones have one of the highest adoption rates of technologies developed within the last century. Digitalization will bring consumers and farmers closer together to access the shortest supply chain possible and reduce rural poverty and hunger. The paper will review the different agricultural technologies and propose a mobile solution, code Sell Harvest, to make farming more sustainable and secure food. Keywords: Sell Harvest, Agriculture, Technology, Artificial Intelligence, and Digital Farming.
As healthcare systems worldwide continue to grapple with the challenges of interoperability, data security, and accessibility, integrating emerging technologies becomes imperative. This paper investigates the implementation of blockchain technology, specifically Hyperledger Fabric, for Electronic Health Records (EHR) management at Frere Hospital in the Eastern Cape province of South Africa. The paper examines the benefits and challenges of integrating blockchain into healthcare information systems. Hyperledger Fabric's modular architecture is harnessed to create a secure, transparent, and decentralized platform for storing, managing, and sharing EHRs among stakeholders. The study used a mixed-methods approach, integrating case studies and data collection methods through observation and informal questions, with the specific goal of understanding current record management methods and challenges. This method offers practical insights and validates the approach. The result demonstrates the role of blockchain in transforming healthcare, framed within a rigorous exploration and analysis. The findings of this study have broader implications for healthcare institutions seeking advanced solutions to address the persistent challenges in electronic health record management. Ultimately, the research underscores the transformative potential of blockchain technology in healthcare settings, fostering trust, security, and efficiency in the management of sensitive patient data.
A vaccine passport serves as documentary proof, providing passport holders with greater freedom while roaming around during pandemics. It confirms vaccination against certain infectious diseases like COVID-19, Ebola, and flu. The key challenges faced by the digital vaccine passport system include passport forgery, unauthorized data access, and inaccurate information input by vaccination centers. Privacy concerns also need to be addressed to ensure that the user's personal identification information (PII) is not compromised. Additionally, it is necessary to track vaccine vials or doses to verify their authenticity, prevent misuse and illegal sales, as well as to restrict the illicit distribution of vaccines. To address these challenges, we propose a Blockchain-Enabled Secure Vaccine Passport System, leveraging the power of smart contracts. Our solution integrates off-chain and on-chain cryptographic computations, facilitating secure communication among various entities. We have utilized the InterPlanetary File System (IPFS) to store encrypted vaccine passports of citizens securely. Our prototype is built on the Ethereum platform, with smart contracts deployed on the Sepolia Test network, allowing for performance evaluation and validation of the system's effectiveness. By combining IPFS as a distributed data storage platform and Ethereum as a blockchain platform, our solution paves the way for secure, efficient, and globally interoperable vaccine passport management, supporting comprehensive vaccination initiatives worldwide.
The advent of blockchain technology and its adoption across various sectors have raised critical discussions about the need for regulatory mechanisms to ensure consumer protection, maintain financial stability, and address privacy concerns without compromising the foundational principles of decentralization and immutability inherent in blockchain platforms. We examine the existing mechanisms for smart contract termination across several major blockchain platforms, including Ethereum, BNB Smart Chain, Cardano, Solana, Hyperledger Fabric, Corda, IOTA, Apotos, and Sui. We assess the compatibility of these mechanisms with the requirements of the EU Data Act, focusing on aspects such as consumer protection, error correction, and regulatory compliance. Our analysis reveals a diverse landscape of approaches, from immutable smart contracts with built-in termination conditions to upgradable smart contracts that allow for post-deployment modifications. We discuss the challenges associated with implementing the so-called smart contract "kill switches," such as the balance between enabling regulatory compliance and preserving the decentralized ethos, the technical feasibility of such mechanisms, and the implications for security and trust in the ecosystem.
Linh Tran, Sanjay Chari, Md. Saikat Islam Khan, Aaron Zachariah · 6 authors
We present the Differentially Private Blockchain-Based Vertical Federal Learning (DP-BBVFL) algorithm that provides verifiability and privacy guarantees for decentralized applications. DP-BBVFL uses a smart contract to aggregate the feature representations, i.e., the embeddings, from clients transparently. We apply local differential privacy to provide privacy for embeddings stored on a blockchain, hence protecting the original data. We provide the first prototype application of differential privacy with blockchain for vertical federated learning. Our experiments with medical data show that DP-BBVFL achieves high accuracy with a tradeoff in training time due to on-chain aggregation. This innovative fusion of differential privacy and blockchain technology in DP-BBVFL could herald a new era of collaborative and trustworthy machine learning applications across several decentralized application domains.
Decentralized Intelligence Network (DIN) is a theoretical framework designed to address challenges in AI development, particularly focusing on data fragmentation and siloing issues. It facilitates effective AI training within sovereign data networks by overcoming barriers to accessing diverse data sources, leveraging: 1) personal data stores to ensure data sovereignty, where data remains securely within Participants' control; 2) a scalable federated learning protocol implemented on a public blockchain for decentralized AI training, where only model parameter updates are shared, keeping data within the personal data stores; and 3) a scalable, trustless cryptographic rewards mechanism on a public blockchain to incentivize participation and ensure fair reward distribution through a decentralized auditing protocol. This approach guarantees that no entity can prevent or control access to training data or influence financial benefits, as coordination and reward distribution are managed on the public blockchain with an immutable record. The framework supports effective AI training by allowing Participants to maintain control over their data, benefit financially, and contribute to a decentralized, scalable ecosystem that leverages collective AI to develop beneficial algorithms.
The rapid advancements in artificial intelligence, big data analytics, and cloud computing have precipitated an unprecedented demand for computational resources. However, the current landscape of computational resource allocation is characterized by significant inefficiencies, including underutilization and price volatility. This paper addresses these challenges by introducing a novel global platform for the commodification of compute hours, termed the Global Compute Exchange (GCX) (Patent Pending). The GCX leverages blockchain technology and smart contracts to create a secure, transparent, and efficient marketplace for buying and selling computational power. The GCX is built in a layered fashion, comprising Market, App, Clearing, Risk Management, Exchange (Offchain), and Blockchain (Onchain) layers, each ensuring a robust and efficient operation. This platform aims to revolutionize the computational resource market by fostering a decentralized, efficient, and transparent ecosystem that ensures equitable access to computing power, stimulates innovation, and supports diverse user needs on a global scale. By transforming compute hours into a tradable commodity, the GCX seeks to optimize resource utilization, stabilize pricing, and democratize access to computational resources. This paper explores the technological infrastructure, market potential, and societal impact of the GCX, positioning it as a pioneering solution poised to drive the next wave of innovation in commodities and compute.
Mohamed Salah Bouafif, Chen Zheng, Ilham Ahmed Qasse, Ed Zulkoski · 6 authors
The surge in the adoption of smart contracts necessitates rigorous auditing to ensure their security and reliability. Manual auditing, although comprehensive, is time-consuming and heavily reliant on the auditor's expertise. With the rise of Large Language Models (LLMs), there is growing interest in leveraging them to assist auditors in the auditing process (co-auditing). However, the effectiveness of LLMs in smart contract co-auditing is contingent upon the design of the input prompts, especially in terms of context description and code length. This paper introduces a novel context-driven prompting technique for smart contract co-auditing. Our approach employs three techniques for context scoping and augmentation, encompassing code scoping to chunk long code into self-contained code segments based on code inter-dependencies, assessment scoping to enhance context description based on the target assessment goal, thereby limiting the search space, and reporting scoping to force a specific format for the generated response. Through empirical evaluations on publicly available vulnerable contracts, our method demonstrated a detection rate of 96\% for vulnerable functions, outperforming the native prompting approach, which detected only 53\%. To assess the reliability of our prompting approach, manual analysis of the results was conducted by expert auditors from our partner, Quantstamp, a world-leading smart contract auditing company. The experts' analysis indicates that, in unlabeled datasets, our proposed approach enhances the proficiency of the GPT-4 code interpreter in detecting vulnerabilities.
Modern blockchain, such as Ethereum, supports the deployment and execution of so-called smart contracts, autonomous digital programs with significant value of cryptocurrency. Executing smart contracts requires gas costs paid by users, which define the limits of the contract's execution. Logic vulnerabilities in smart contracts can lead to financial losses, and are often the root cause of high-impact cyberattacks. Our objective is threefold: (i) empirically investigate logic vulnerabilities in real-world smart contracts extracted from code changes on GitHub, (ii) introduce Soley, an automated method for detecting logic vulnerabilities in smart contracts, leveraging Large Language Models (LLMs), and (iii) examine mitigation strategies employed by smart contract developers to address these vulnerabilities in real-world scenarios. We obtained smart contracts and related code changes from GitHub. To address the first and third objectives, we qualitatively investigated available logic vulnerabilities using an open coding method. We identified these vulnerabilities and their mitigation strategies. For the second objective, we extracted various logic vulnerabilities, applied preprocessing techniques, and implemented and trained the proposed Soley model. We evaluated Soley along with the performance of various LLMs and compared the results with the state-of-the-art baseline on the task of logic vulnerability detection. From our analysis, we identified nine novel logic vulnerabilities, extending existing taxonomies with these vulnerabilities. Furthermore, we introduced several mitigation strategies extracted from observed developer modifications in real-world scenarios. Our Soley method outperforms existing methods in automatically identifying logic vulnerabilities. Interestingly, the efficacy of LLMs in this task was evident without requiring extensive feature engineering.
The entry of new technological infrastructures into the financial markets poses serious concerns about the misuse of the economic system for illicit purposes, such as money laundering and financing of terrorism. Although there are cases in which this connection has already been discovered by malicious actors, distributed ledger technologies can nevertheless represent a powerful tool at the disposal of competent authorities to trace illicit flows and to better monitor risks in financial markets. However, this possibility may go through an interdisciplinary analysis of the phenomena. The search for alternative systems to move funds, rather than the traditional financial intermediaries, such as banks, is not a new circumstance and not necessarily for criminal purposes. Nevertheless, some of the already-known value transfer systems may benefit from the use of distributed ledger technology and make their detection more difficult. The European institutions are discussing the needed legislative packages to enforce the current regulations and to extend their application to the crypto space, as well as the establishment of a new competent authority.
A Service Level Agreement (SLA) is a commitment between a client and provider that assures the quality of service (QoS) a client can expect to receive when purchasing a service. However, evidence of SLA violations in Internet of Things (IoT) service monitoring data can be manipulated by the provider or consumer, resulting in an issue of trust between contracted parties. The following research aims to explore the use of blockchain technology in monitoring IoT systems using smart contracts so that SLA violations captured are irrefutable amongst service providers and clients. The research focuses on the development of a Java library that is capable of generating a smart contract from a given SLA. A smart contract generated by this library is validated through a mock scenario presented in the form of a Remote Patient Monitoring IoT system. In this scenario, the findings demonstrate a 100 percent success rate in capturing all emulated violations.
Industry 4.0 and beyond will rely heavily on sustainable Business Decision Modelling (BDM) that can be accelerated by blockchain and Digital Twin (DT) solutions. BDM is built on models and frameworks refined by key identification factors, data analysis, and mathematical or computational aspects applicable to complex business scenarios. Gaining actionable intelligence from collected data for BDM requires a carefully considered infrastructure to ensure data transparency, security, accessibility and sustainability. Organisations should consider social, economic and environmental factors (based on the triple bottom line approach) to ensure sustainability when integrating such an infrastructure. These sustainability features directly impact BDM concerning resource optimisation, stakeholder engagement, regulatory compliance and environmental impacts. To further understand these segments, taxonomies are defined to evaluate blockchain and DT sustainability features based on an in-depth review of the current state-of-the-art research. Detailed comparative evaluations provide insight into the reachability of the sustainable solution in terms of ideologies, access control and performance overheads. Several research questions are put forward to motivate further research that significantly impacts BDM. Finally, a case study based on an exemplary supply chain management system is presented to show the interoperability of blockchain and DT with BDM.
May 9, 2024·Rehak, Rainer (2019) A Trustless Society. A political look at the blockchain vision, BZH Beitraege zur Hochschulforschung, Issue 3/2019, pp. 60-65
A lot of business and research effort currently deals with the so called decentralised ledger technology blockchain. Putting it to use carries the tempting promise to make the intermediaries of social interactions superfluous and furthermore keep secure track of all interactions. Currently intermediaries such as banks and notaries are necessary and must be trusted, which creates great dependencies, as the financial crisis of 2008 painfully demonstrated. Especially banks and notaries are said to become dispensable as a result of using the blockchain. But in real-world applications of the blockchain, the power of central actors does not dissolve, it only shifts to new, democratically illegitimate, uncontrolled or even uncontrollable power centers. As interesting as the blockchain technically is, it doesn't efficiently solve any real-world problem and is no substitute for traditional political processes or democratic regulation of power. Research efforts investigating the blockchain should be halted.
Large Language Models (LLMs) have witnessed rapid growth in emerging challenges and capabilities of language understanding, generation, and reasoning. Despite their remarkable performance in natural language processing-based applications, LLMs are susceptible to undesirable and erratic behaviors, including hallucinations, unreliable reasoning, and the generation of harmful content. These flawed behaviors undermine trust in LLMs and pose significant hurdles to their adoption in real-world applications, such as legal assistance and medical diagnosis, where precision, reliability, and ethical considerations are paramount. These could also lead to user dissatisfaction, which is currently inadequately assessed and captured. Therefore, to effectively and transparently assess users' satisfaction and trust in their interactions with LLMs, we design and develop LLMChain, a decentralized blockchain-based reputation system that combines automatic evaluation with human feedback to assign contextual reputation scores that accurately reflect LLM's behavior. LLMChain not only helps users and entities identify the most trustworthy LLM for their specific needs, but also provides LLM developers with valuable information to refine and improve their models. To our knowledge, this is the first time that a blockchain-based distributed framework for sharing and evaluating LLMs has been introduced. Implemented using emerging tools, LLMChain is evaluated across two benchmark datasets, showcasing its effectiveness and scalability in assessing seven different LLMs.
Bruno Ramos-Cruz, Javier Andreu-Pérez, Francisco J. Quesada, Luis Martı́nez
Blockchain technology has become a trusted method for establishing secure and transparent transactions through a distributed, encrypted network. The operation of blockchain is governed by consensus algorithms, among which Proof of Stake (PoS) is popular yet has its drawbacks, notably the potential for centralising power in nodes with larger stakes or higher rewards. Our proposed novel solution, Fuzzychain, leverages fuzzy sets to define stake semantics, introducing a degree of softness in validator selection. This approach mitigates rigid threshold-based decision-making by allowing gradual transitions between stake levels, reducing sharp disparities among validators. By incorporating this enhanced stake evaluation, Fuzzychain promotes a more adaptive and distributed selection process, ensuring a fairer and more inclusive blockchain network. A thorough assessment of a real-time multi-agent blockchain system to examine validator selection and reduce inequality, promoting a more equitable distribution of stakes among validators compared to other consensus mechanisms. This fosters a more inclusive selection process and a more equitably distributed network.
Kostas Kryptos Chalkias, Angelos Kostis, Ali Alnuaimi, Peter Knez · 8 authors
In the contemporary era, biodiversity conservation emerges as a paramount challenge, necessitating innovative approaches to monitoring, preserving, and enhancing the natural world. This paper explores the integration of blockchain technology in biodiversity conservation, offering a novel perspective on how digital resilience can be built within ecological contexts. Blockchain, with its decentralized and immutable ledger and tokenization affordances, presents a groundbreaking solution for the accurate monitoring and tracking of environmental assets, thereby addressing the critical need for transparency and trust in conservation efforts. Unlike previous more theoretical approaches, by addressing the research question of how blockchain supports digital resilience in biodiversity conservation, this study presents a grounded framework that justifies which blockchain features are essential to decipher specific data contribution and data leveraging processes in an effort to protect our planet's biodiversity, while boosting potential economic benefits for all actors involved, from local farmers, to hardware vendors and artificial intelligence experts, to investors and regular users, volunteers and donors.